Abstract
Oil Spill Risk Assessments (OSRAs) are widely employed to support decision making regarding oil spill risks. This article adapts the ISO-compliant OSRA framework developed by Sepp Neves et al. (J Environ Manag 159:158–168, 2015) to estimate risks in a complex scenario where uncertainties related to the meteo-oceanographic conditions, where and how a spill could happen exist and the risk computation methodology is not yet well established (ensemble oil spill modeling). The improved method was applied to the Algarve coast, Portugal. Over 50,000 simulations were performed in 2 ensemble experiments to estimate the risks due to operational and accidental spill scenarios associated with maritime traffic. The level of risk was found to be important for both types of scenarios, with significant seasonal variations due to the the currents and waves variability. Higher frequency variability in the meteo-oceanographic variables were also found to contribute to the level of risk. The ensemble results show that the distribution of oil concentrations found on the coast is not Gaussian, opening up new fields of research on how to deal with oil spill risks and related uncertainties.
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Acknowledgments
This work was co-funded through the TESSA Project, a MACOMA Grant and the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 633211. MACOMA is a Joint Doctorate program selected under Erasmus Mundus coordinated by the University of Cadiz. “TESSA” (Sviluppo di TEcnologie per la Situational Sea Awareness) is an industrial research project supported by PON “Ricerca & Competitivita 2007–2013” program of the Ministry for Education, University and Research. The authors would also like to thank Catarina Frazao Santos for making the coastal vulnerability data available.
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Responsible Editor: Yajing Yan
This article is part of the Topical Collection on the 47th International Liége Colloquium on Ocean Dynamics, Liège, Belgium, 4–8 May 2015
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Sepp Neves, A.A., Pinardi, N. & Martins, F. IT-OSRA: applying ensemble simulations to estimate the oil spill risk associated to operational and accidental oil spills. Ocean Dynamics 66, 939–954 (2016). https://doi.org/10.1007/s10236-016-0960-0
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DOI: https://doi.org/10.1007/s10236-016-0960-0